Yevhenii
Senior Python Developer and team lead with over 8 years of experience building large-scale data acquisition systems for international companies. Led teams in developing resilient scrapers, AI-powered sentiment analysis platforms, and predictive models for industries ranging from e-commerce to finance. Passionate about turning raw web data into actionable insights, sharing hands-on lessons from real-world projects at the intersection of Python, data engineering, and machine learning.
Session
Companies today are hungry for external data to stay competitive, but actually getting and making sense of that data isn’t easy. Standard web scraping often produces messy or incomplete results, and modern anti-bot systems make reliable collection even tougher.
In this talk, I’ll share how pairing Python’s scraping frameworks (like Scrapy, Playwright, and Selenium) with AI/ML can turn raw, unstructured data into clear, actionable insights.
We’ll look at:
1) How to build scrapers that still work in 2025.
2) Ways to use AI to automatically clean, enrich, and classify data.
3) Real-world applications of sentiment analysis for reviews and social media.
4) Case studies showing how SMEs have used these pipelines to sharpen marketing and product strategies.
By the end, you’ll see how to design pipelines that don’t just gather data, but deliver real strategic value. The session will focus on practical Python tools, scalable deployment (Airflow, Kubernetes, cloud platforms), and key lessons learned from hands-on projects at the intersection of scraping and AI.